Post-Hospitalization Home Monitoring Programs During the COVID-19 Pandemic: Survey Results from the Hospital Medicine Re-engineering Network (HOMERuN).

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, hospitals and healthcare systems launched innovative responses to emerging needs. The creation and use of programs to remotely follow patient clinical status and recovery after COVID-19 hospitalization has not been thoroughly described. OBJECTIVE: To characterize deployment of remote post-hospital discharge monitoring programs during the COVID-19 pandemic METHODS: Electronic surveys were administered to leaders of 83 US academic hospitals in the Hospital Medicine Re-engineering Network (HOMERuN). An initial survey was completed in March 2021 with follow-up survey completed in July 2022. RESULTS: There were 35 responses to the initial survey (42%) and 15 responses to the follow-up survey (43%). Twenty-two (63%) sites reported a post-discharge monitoring program, 16 of which were newly developed for COVID-19. Physiologic monitoring devices such as pulse oximeters were often provided. Communication with medical teams was often via telephone, with moderate use of apps or electronic medical record integration. Programs launched most commonly between January and June 2020. Only three programs were still active at the time of follow-up survey. CONCLUSIONS: Our findings demonstrate rapid, ad hoc development of post-hospital discharge monitoring programs during the COVID-19 pandemic but with little standardization or evaluation. Additional study could identify the benefits of these programs, instruct their potential application to other disease processes, and inform further development as part of emergency preparedness for upcoming crises.

Medically ready for discharge: A multisite "point-in-time" assessment of hospitalized patients.

BACKGROUND: Time spent awaiting discharge after the acute need for hospitalization has resolved is an important potential contributor to hospital length of stay (LOS). OBJECTIVE: To measure the prevalence, impact, and context of patients who remain hospitalized for prolonged periods after completion of acute care needs. DESIGN, SETTING, AND PARTICIPANTS: We conducted a cross-sectional "point-in-time" survey at each of 15 academic US hospitals using a structured data collection tool with on-service acute care medicine attending physicians in fall 2022. MAIN OUTCOMES AND MEASURES: Primary outcomes were number and percentage of patients considered "medically ready for discharge" with emphasis on those who had experienced a "major barrier to discharge" (medically ready for discharge for ≥1 week). Estimated LOS attributable to major discharge barriers, contributory discharge needs, and associated hospital characteristics were measured. RESULTS: Of 1928 patients sampled, 35.0% (n = 674) were medically ready for discharge including 9.8% (n = 189) with major discharge barriers. Many patients with major discharge barriers (44.4%; 84/189) had spent a month or longer medically ready for discharge and commonly (84.1%; 159/189) required some form of skilled therapy or daily living support services for discharge. Higher proportions of patients experiencing major discharge barriers were found in public versus private, nonprofit hospitals (12.0% vs. 7.2%; p = .001) and county versus noncounty hospitals (14.5% vs. 8.8%; p = .002). CONCLUSIONS: Patients experience major discharge barriers in many US hospitals and spend prolonged time awaiting discharge, often for support needs that may be outside of clinician control.

A Description of Mechanically Ventilated Patients Admitted From the Emergency Department With a Short Critical Care Stay.

BACKGROUND: Patients admitted to an intensive care unit (ICU) requiring invasive mechanical ventilation who are discharged alive from the ICU within 24 h are poorly characterized in the literature. OBJECTIVE: Our aim was to characterize a cohort of intubated emergency department (ED) patients who are extubated and discharged from the ICU within 24 h. METHODS: We conducted a retrospective, observational cohort study at a single level I trauma center from January 2017 to December 2019. We included adults who were admitted to an ICU from the ED requiring invasive mechanical ventilation. Our primary outcome was the proportion of patients who were discharged from the ICU alive within 24 h. RESULTS: Of 13,374 ED patients admitted to an ICU during the study period, 2871 patients were intubated and ventilated in the prehospital or ED settings. Of these, 14% were discharged alive from the ICU within 24 h of admission. Only 21% of these patients were intubated in the ED. We identified the following two distinct subpopulations comprising 62% of this short-stay group: patients with a primary discharge diagnosis of intoxication (47%) and minimally injured trauma patients (53%), with 4% of patients in both subgroups. CONCLUSIONS: A total of 14% of patients receiving intubation with mechanical ventilation in the prehospital environment or in the ED were discharged alive from the ICU within 24 h. We identified two distinct subgroups of patients with a short stay in intensive care who may be candidates for ED extubation, including patients with intoxication and minimally injured trauma patients.

From Battles to Burnout: Investigating the Role of Interphysician Conflict in Physician Burnout.

PURPOSE: Despite the recognized importance of collaborative communication among physicians, conflict at transitions of care remains a pervasive issue. Recent work has underscored how poor communication can undermine patient safety and organizational efficiency, yet little is known about how interphysician conflict (I-PC) impacts the physicians forced to navigate these tensions. The goal of this study was to explore the social processes and interpersonal interactions surrounding I-PC and their impact, using conversations regarding admission between internal medicine (IM) and emergency medicine (EM) as a lens to explore I-PC in clinical practice. METHOD: The authors used constructivist grounded theory to explore the interpersonal and social dynamics of I-PC. They used purposive sampling to recruit participants, including EM resident and attending physicians and IM attending physicians. The authors conducted hour-long, semistructured interviews between June and October 2020 using the Zoom video conferencing platform. Interviews were coded in 3 phases: initial line-by-line coding, focused coding, and recording. Constant comparative analysis was used to refine emerging codes, and the interview guide was iteratively updated. RESULTS: The authors interviewed 18 residents and attending physicians about how engaging in I-PC led to both personal and professional harm. Specifically, physicians described how I-PC resulted in emotional distress, demoralization, diminished sense of professional attributes, and job dissatisfaction. Participants also described how emotional residue attached to past I-PC events primed the workplace for future conflict. CONCLUSIONS: I-PC may represent a serious yet underrecognized source of harm, not only to patient safety but also to physician well-being. Participants described both the personal and professional consequences of I-PC, which align with the core tenets of burnout. Burnout is a well-established threat to the physician workforce, but unlike many other contributors to burnout, I-PC may be modifiable through improved education that equips physicians with the skills to navigate I-PC throughout their careers.

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015-2019 in 2 integrated health-care institutions in the Northwest United States. We used one site's manually reviewed gold-standard outcomes data for model development and the other's for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.

Validation of Acute Pancreatitis Among Adults in an Integrated Healthcare System.

BACKGROUND: Acute pancreatitis is a serious gastrointestinal disease that is an important target for drug safety surveillance. Little is known about the accuracy of ICD-10 codes for acute pancreatitis in the United States, or their performance in specific clinical settings. We conducted a validation study to assess the accuracy of acute pancreatitis ICD-10 diagnosis codes in inpatient, emergency department (ED), and outpatient settings. METHODS: We reviewed electronic medical records for encounters with acute pancreatitis diagnosis codes in an integrated healthcare system from October 2015 to December 2019. Trained abstractors and physician adjudicators determined whether events met criteria for acute pancreatitis. RESULTS: Out of 1,844 eligible events, we randomly sampled 300 for review. Across all clinical settings, 182 events met validation criteria for an overall positive predictive value (PPV) of 61% (95% confidence intervals [CI] = 55, 66). The PPV was 87% (95% CI = 79, 92%) for inpatient codes, but only 45% for ED (95% CI = 35, 54%) and outpatient (95% CI = 34, 55%) codes. ED and outpatient encounters accounted for 43% of validated events. Acute pancreatitis codes from any encounter type with lipase >3 times the upper limit of normal had a PPV of 92% (95% CI = 86, 95%) and identified 85% of validated events (95% CI = 79, 89%), while codes with lipase <3 times the upper limit of normal had a PPV of only 22% (95% CI = 16, 30%). CONCLUSIONS: These results suggest that ICD-10 codes accurately identified acute pancreatitis in the inpatient setting, but not in the ED and outpatient settings. Laboratory data substantially improved algorithm performance.

Clinical risk calculators informing the decision to admit: A methodologic evaluation and assessment of applicability.

INTRODUCTION: Clinical prediction and decision tools that generate outcome-based risk stratification and/or intervention recommendations are prevalent. Appropriate use and validity of these tools, especially those that inform complex clinical decisions, remains unclear. The objective of this study was to assess the methodologic quality and applicability of clinical risk scoring tools used to guide hospitalization decision-making. METHODS: In February 2021, a comprehensive search was performed of a clinical calculator online database (mdcalc.com) that is publicly available and well-known to clinicians. The primary reference for any calculator tool informing outpatient versus inpatient disposition was considered for inclusion. Studies were restricted to the adult, acute care population. Those focused on obstetrics/gynecology or critical care admission were excluded. The Wasson-Laupacis framework of methodologic standards for clinical prediction rules was applied to each study. RESULTS: A total of 22 calculators provided hospital admission recommendations for 9 discrete medical conditions using adverse events (14/22), mortality (6/22), or confirmatory diagnosis (2/22) as outcomes of interest. The most commonly met methodologic standards included mathematical technique description (22/22) and clinical sensibility (22/22) and least commonly met included reproducibility of the rule (1/22) and measurement of effect on clinical use (1/22). Description of the studied population was often lacking, especially patient race/ethnicity (2/22) and mental or behavioral health (0/22). Only one study reported any item related to social determinants of health. CONCLUSION: Studies commonly do not meet rigorous methodologic standards and often fail to report pertinent details that would guide applicability. These clinical tools focus primarily on specific disease entities and clinical variables, missing the breadth of information necessary to make a disposition determination and raise significant validation and generalizability concerns.

Implementing a Social Determinants of Health Curriculum in Undergraduate Medical Education: A Qualitative Analysis of Faculty Experience.

PURPOSE: Following shifts that broadened the medical profession's conceptualization of the underlying drivers of health, medical schools are required to integrate curricula on health disparities and the social context of medicine into undergraduate medical education. Although previous research has focused on student experiences and outcomes in these curricula, less attention has been paid to the experiences of the physician-faculty involved. This study aimed to capture faculty insights to improve understanding of the challenges and opportunities of implementing this curricular reform. METHOD: In-depth, semistructured interviews were conducted with 10 faculty members at one U.S. medical school in spring 2019 to capture their experiences designing and teaching a new curriculum related to the social determinants of health and health disparities. Study design, including interview guide development, was informed by the critical pedagogy perspective and social constructionist approaches to curriculum implementation. With the use of a constructivist grounded theory approach, interview transcripts were analyzed using open, thematic, and axial coding techniques. Primary themes were categorized as professional, organizational, interactional, or intrapersonal and organized into the final model. RESULTS: Participants processed their experiences at 4 concentric levels: professional, organizational, interactional, and intrapersonal. Faculty generally embraced the movement to incorporate more discussion of social context as a driver of health outcomes. However, they struggled with the shortcomings of their training and navigating structural constraints within their school when developing and delivering content. When confronted with these limitations, faculty experienced unexpected tension in the classroom setting that catalyzed self-reflection and reconstruction of their teaching approach. CONCLUSIONS: Findings highlight the challenges that faculty encounter when integrating social determinants of health and related curricula into undergraduate medical education. They also speak to the need for a broader conceptualization of relevant expertise and have implications for how medical schools select, train, and support medical educators in this work.

Who's on your team? Specialty identity and inter-physician conflict during admissions.

PURPOSE: Despite the implementation of professionalism curricula and standardised communication tools, inter-physician conflict persists. In particular, the interface between emergency medicine (EM) and internal medicine (IM) has long been recognised as a source of conflict. The social nuances of this conflict remain underexplored, limiting educators' ability to comprehensively address these issues in the clinical learning environment. Thus, the authors explored EM and IM physicians' experiences with negotiating hospital admissions to better understand the social dynamics that contribute to inter-physician conflict and provide foundational guidance for communication best practices. METHODS: Using a constructivist grounded theory (CGT) approach, the authors conducted 18 semi-structured interviews between June and October 2020 with EM and IM physicians involved in conversations regarding admissions (CRAs). They asked participants to describe the social exchanges that influenced these conversations and to reflect on their experiences with inter-physician conflict. Data collection and analysis occurred iteratively. The relationships between the codes were discussed by the research team with the goal of developing conceptual connections between the emergent themes. RESULTS: Participants described how their approaches to CRAs were shaped by their specialty identity, and how allegiance to members of their group contributed to interpersonal conflict. This conflict was further promoted by a mutual sense of disempowerment within the organisation, misaligned expectations, and a desire to promote their group's prerogatives. Conflict was mitigated when patient care experiences fostered cross-specialty team formation and collaboration that dissolved traditional group boundaries. CONCLUSIONS: Conflict between EM and IM physicians during CRAs was primed by participants' specialty identities, their power struggles within the broader organisation, and their sense of duty to their own specialty. However, formation of collaborative inter-specialty physician teams and expansion of identity to include colleagues from other specialties can mitigate inter-physician conflict.

Qualitative analysis of disposition decision making for patients referred for admission from the emergency department without definite medical acuity.

OBJECTIVE: To map the physician approach when determining disposition for a patient who presents without the level of definite medical acuity that would generally warrant hospitalisation. DATA SOURCES/STUDY SETTING: Since 2018, our US academic county hospital/trauma centre has maintained a database in which hospitalists ('triage physicians') document the rationale and outcomes of requests for admission to the acute care medical ward during each shift. STUDY DESIGN: Narrative text from the database was analysed using a grounded theory approach to identify major themes and subthemes, and a conceptual model of the admission decision-making process was constructed. PARTICIPANTS: Database entries were included (n=300) if the admission call originated from the emergency department and if the triage physician characterised the request as potentially inappropriate because the patient did not have definite medical acuity. RESULTS: Admission decision making occurs in three main phases: evaluation of unmet needs, assessment of risk and re-evaluation. Importantly, admission decision making is not solely based on medical acuity or clinical algorithms, and patients without a definite medical need for admission are hospitalised when physicians believe a potential issue exists if discharged. In this way, factors such as homelessness, substance use disorder, frailty, etc, contribute to admission because they raise concern about patient safety and/or barriers to appropriate treatment. Physician decision making can be altered by activities such as care coordination, advocacy by the patient or surrogate, interactions with other physicians or a change in clinical trajectory. CONCLUSIONS: The decision to admit ultimately remains a clinical determination constructed between physician and patient. Physicians use a holistic process that incorporates broad consideration of the patient's medical and social needs with emphasis on risk assessment; thus, any analysis of hospitalisation trends or efforts to impact such should seek to understand this individual-level decision making.

Discharge Practices for COVID-19 Patients: Rapid Review of Published Guidance and Synthesis of Documents and Practices at 22 US Academic Medical Centers.

BACKGROUND: There are currently no evidence-based guidelines that provide standardized criteria for the discharge of COVID-19 patients from the hospital. OBJECTIVE: To address this gap in practice guidance, we reviewed published guidance and collected discharge protocols and procedures to identify and synthesize common practices. DESIGN: Rapid review of existing guidance from US and non-US public health organizations and professional societies and qualitative review using content analysis of discharge documents collected from a national sample of US academic medical centers with follow-up survey of hospital leaders SETTING AND PARTICIPANTS: We reviewed 65 websites for major professional societies and public health organizations and collected documents from 22 Academic Medical Centers (AMCs) in the US participating in the HOspital MEdicine Reengineering Network (HOMERuN). RESULTS: We synthesized data regarding common practices around 5 major domains: (1) isolation and transmission mitigation; (2) criteria for discharge to non-home settings including skilled nursing, assisted living, or homeless; (3) clinical criteria for discharge including oxygenation levels, fever, and symptom improvement; (4) social support and ability to perform activities of daily living; (5) post-discharge instructions, monitoring, and follow-up. LIMITATIONS: We used streamlined methods for rapid review of published guidance and collected discharge documents only in a focused sample of US academic medical centers. CONCLUSION: AMCs studied showed strong consensus on discharge practices for COVID-19 patients related to post-discharge isolation and transmission mitigation for home and non-home settings. There was high concordance among AMCs that discharge practices should address COVID-19-specific factors in clinical, functional, and post-discharge monitoring domains although definitions and details varied.

Identification and Validation of Anaphylaxis Using Electronic Health Data in a Population-based Setting.

BACKGROUND: Anaphylaxis is a life-threatening allergic reaction that is difficult to identify accurately with administrative data. We conducted a population-based validation study to assess the accuracy of ICD-10 diagnosis codes for anaphylaxis in outpatient, emergency department, and inpatient settings. METHODS: In an integrated healthcare system in Washington State, we obtained medical records from healthcare encounters with anaphylaxis diagnosis codes (potential events) from October 2015 to December 2018. To capture events missed by anaphylaxis diagnosis codes, we also obtained records on a sample of serious allergic and drug reactions. Two physicians determined whether potential events met established clinical criteria for anaphylaxis (validated events). RESULTS: Out of 239 potential events with anaphylaxis diagnosis codes, the overall positive predictive value (PPV) for validated events was 64% (95% CI = 58 to 70). The PPV decreased with increasing age. Common precipitants for anaphylaxis were food (39%), medications (35%), and insect bite or sting (12%). The sensitivity of emergency department and inpatient anaphylaxis diagnosis codes for all validated events was 58% (95% CI = 51 to 65), but sensitivity increased to 95% (95% CI = 74 to 99) when outpatient diagnosis codes were included. Using information from all validated events and sampling weights, the incidence rate for anaphylaxis was 3.6 events per 10,000 person-years (95% CI = 3.1 to 4.0). CONCLUSIONS: In this population-based setting, ICD-10 diagnosis codes for anaphylaxis from emergency department and inpatient settings had moderate PPV and sensitivity for validated events. These findings have implications for epidemiologic studies that seek to estimate risks of anaphylaxis using electronic health data.

Factors associated with low-acuity hospital admissions in a public safety-net setting: a cross-sectional study.

BACKGROUND: Given system-level focus on avoidance of unnecessary hospitalizations, better understanding admission decision-making is of utility. Our study sought to identify factors associated with hospital admission versus discharge from the Emergency Department (ED) for a population of patients who were assessed as having low medical acuity at time of decision. METHODS: Using an institutional database, we identified ED admission requests received from March 1, 2018 to Feb 28, 2019 that were assessed by a physician at the time of request as potentially inappropriate based on lack of medical acuity. Focused chart review was performed to extract data related to patient demographics, socioeconomic information, measures of illness, and system-level factors such as previous healthcare utilization and day/time of presentation. A binary logistic regression model was constructed to correlate patient and system factors with disposition outcome of admission to the hospital versus discharge from the ED. Physician-reported contributors to admission decision-making and chief complaint/reason for admission were summarized. RESULTS: A total of 349 (77.2%) of 452 calls resulted in admission to the hospital and 103 (22.8%) resulted in discharge from the ED. Predictors of admission included age over 65 (OR 3.5 [95%CI 1.1-11.6], p = 0.039), homelessness (OR 3.3 [95% CI 1.7-6.4], p=0.001), and night/weekend presentation (OR 2.0 [95%CI 1.1-3.5], p = 0.020). The most common contributing factors to the decision to admit reported by the responding physician included: lack of outpatient social support (35.8% of admissions), homelessness (33.0% of admissions), and substance use disorder (23.5% of admissions). CONCLUSIONS: Physician medical decision-making regarding the need for hospitalization incorporates consideration of individual patient characteristics, social setting, and system-level barriers. Interventions aimed at reducing unnecessary hospitalizations, especially those involving patients with low medical acuity, should focus on underlying unmet needs and involve a broad set of perspectives.